Structure-based elucidation of thiazine inhibitors targeting estrogen receptors alpha: pharmacophore modeling, virtual screening, molecular docking, MD, and DFT approach.

Structure-Based In Silico Screening of PubChem Compounds for Potential Anti-Inflammatory and Anticancer Targets

C25, the pyrazolin derivative represents a novel multi-target ligand with potential applications as an anti-inflammatory, analgesic, and anti-neoplastic agent and highlights its promise as a lead scaffold for future drug development.

Computational identification of potential VEGFR2 inhibitors using integrated pharmacophore modeling, QSAR analysis, molecular docking, dynamics simulation, and virtual screening followed by in vitro bioassays

Tetrazole–imidazole hybrid derivatives as potential EGFR tyrosine kinase inhibitors: design, synthesis and in silico evaluation with preliminary antiproliferative assessment

Identification of novel EGFR inhibitors for glioblastoma through pharmacophore-guided virtual screening and molecular dynamics

The pharmacophore-based screening and docking analysis identified eleven promising EGFR-binding compounds, of which eight demonstrated optimal ADMET characteristics and stable interactions within the active site during molecular dynamics simulations, suggesting their potential efficacy as EGFR inhibitors.

MOLECULAR DOCKING STUDY OF INDONESIAN PLANT-DERIVED BIOACTIVE COMPOUND TARGETING ESTROGEN RECEPTOR ALPHA (1L2J) IN CERVICAL CANCER

Findings suggest that carissanol from Carissa spinarum L. is a promising natural lead compound targeting ER-?

In-silico Molecular Docking and ADME/Pharmacokinetic Prediction Studies of Some Novel Benzothiazole Derivatives as Anticancer Agents for the Treatment of Breast Cancer

Molecular docking simulation of 3 molecules of N-(1H-benzo[d]imidazol-2-yl)-7-chloro-6-fluorobenzo[d]thiazol2-amine with the target receptor aromatase was carried out so as to evaluate their theoretical binding affinities. The chemical structure of the molecules was accurately drawn using ChemDraw Ultra software, then optimized at density functional theory (DFT) using Becke’s three-parameter Lee–Yang–Parr hybrid functional (B3LYP/6-311**) basis set in a vacuum of Spartan 14 software. Subsequently, the docking operation was carried out using PyRx virtual screening software. Three compounds were developed by fusion of a benzothiazole and benzimidazole ring system targeting the treatment of breast cancer. The marketed drug Exemestane which is also an aromatase inhibitor was used as a reference molecule for docking. The highest docking score from all three molecules was -8.6 kcal/mol which is very near to the standard drug score -9.5 kcal/mol which suggests that the compound exhibited favorable protein–ligand interactions, indicating its potential as a lead candidate for further investigation. In-silico ADME and drug-likeness prediction of the molecules showed good pharmacokinetic properties having high gastrointestinal absorption, orally bioavailable, and less toxic. The outcome of the present research strengthens the relevance of these compounds as promising lead candidates for the treatment of breast cancer which could help the medicinal chemists and pharmaceutical professionals in further designing and synthesis of more potent drug candidates. Moreover, the research also encouraged the in vivo and in vitro evaluation study for the proposed designed compounds to validate the computational findings.